Just a collection of some random cool stuff. PS. Almost 99% of the contents here are not mine and I don't take credit for them, I reference and copy part of the interesting sections.
Friday, November 28, 2014
Continuous integration servers
Jenkins
http://jenkins-ci.org/
Bamboo
https://confluence.atlassian.com/display/BAMBOO/Bamboo+Documentation+Home
Wednesday, November 26, 2014
PLOS Computational Biology: Translational Bioinformatics
http://www.ploscollections.org/article/browseIssue.action?issue=info:doi/10.1371/issue.pcol.v03.i11
Let's Make Those Book Chapters Open Too!
Philip E. Bourne
PLOS Computational Biology: published 21 Feb 2013 | info:doi/10.1371/journal.pcbi.1002941
Education Articles
Introduction to Translational Bioinformatics Collection
Russ B. Altman
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002796
Chapter 1: Biomedical Knowledge Integration
Philip R. O. Payne
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002826
Chapter 2: Data-Driven View of Disease Biology
Casey S. Greene, Olga G. Troyanskaya
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002816
Chapter 3: Small Molecules and Disease
David S. Wishart
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002805
Chapter 4: Protein Interactions and Disease
Mileidy W. Gonzalez, Maricel G. Kann
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002819
Chapter 5: Network Biology Approach to Complex Diseases
Dong-Yeon Cho, Yoo-Ah Kim, Teresa M. Przytycka
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002820
Chapter 6: Structural Variation and Medical Genomics
Benjamin J. Raphael
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002821
Chapter 7: Pharmacogenomics
Konrad J. Karczewski, Roxana Daneshjou, Russ B. Altman
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002817
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002858
Chapter 9: Analyses Using Disease Ontologies
Nigam H. Shah, Tyler Cole, Mark A. Musen
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002827
Chapter 10: Mining Genome-Wide Genetic Markers
Xiang Zhang, Shunping Huang, Zhaojun Zhang, Wei Wang
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002828
Chapter 11: Genome-Wide Association Studies
William S. Bush, Jason H. Moore
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002822
Chapter 12: Human Microbiome Analysis
Xochitl C. Morgan, Curtis Huttenhower
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002808
Chapter 13: Mining Electronic Health Records in the Genomics Era
Joshua C. Denny
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002823
Chapter 14: Cancer Genome Analysis
Miguel Vazquez, Victor de la Torre, Alfonso Valencia
PLOS Computational Biology: published 27 Dec 2012 | info:doi/10.1371/journal.pcbi.1002824
Chapter 15: Disease Gene Prioritization
Yana Bromberg
PLOS Computational Biology: published 25 Apr 2013 | info:doi/10.1371/journal.pcbi.1002902
Chapter 16: Text Mining for Translational Bioinformatics
K. Bretonnel Cohen, Lawrence E. Hunter
PLOS Computational Biology: published 25 Apr 2013 | info:doi/10.1371/journal.pcbi.1003044
Chapter 17: Bioimage Informatics for Systems Pharmacology
Fuhai Li, Zheng Yin, Guangxu Jin, Hong Zhao, Stephen T. C. Wong
PLOS Computational Biology: published 25 Apr 2013 | info:doi/10.1371/journal.pcbi.1003043
Thursday, November 20, 2014
threejs - makes WebGL - 3D in the browser - very easy
http://threejs.org/docs/index.html#Manual/Introduction/Creating_a_scene
Three.js is a library that makes WebGL - 3D in the browser - very easy. While a simple cube in raw WebGL would turn out hundreds of lines of Javascript and shader code, a Three.js equivalent is only a fraction of that.
Three.js is a library that makes WebGL - 3D in the browser - very easy. While a simple cube in raw WebGL would turn out hundreds of lines of Javascript and shader code, a Three.js equivalent is only a fraction of that.
Google Genomics
https://cloud.google.com/genomics/v1beta2/visualization
Google Genomics provides an API to store, process, explore, and share DNA sequence reads, reference-based alignments, and variant calls, using Google's cloud infrastructure.
Store alignments and variant calls for one genome or a million.
Process genomic data in batch by running principal component analysis or Hardy-Weinberg equilibrium, in minutes or hours, by using parallel computing frameworks like MapReduce.
Explore data by slicing alignments and variants by genomic range across one or multiple samples -- for your own algorithms or for visualization; or interactively process entire cohorts to find transition/transversion ratios, allelic frequency, genome-wide association and more using BigQuery.
Share genomic data with your research group, collaborators, the broader community, or the public. You decide.
Google Genomics is implementing the API defined by the Global Alliance for Genomics and Health for visualization, analysis and more. Compliant software can access Google Genomics, local servers, or any other implementation.
Cluster computing
https://spark.apache.org/downloads.html
Google BigQuery
https://cloud.google.com/bigquery/what-is-bigquery
Google Genomics provides an API to store, process, explore, and share DNA sequence reads, reference-based alignments, and variant calls, using Google's cloud infrastructure.
Store alignments and variant calls for one genome or a million.
Process genomic data in batch by running principal component analysis or Hardy-Weinberg equilibrium, in minutes or hours, by using parallel computing frameworks like MapReduce.
Explore data by slicing alignments and variants by genomic range across one or multiple samples -- for your own algorithms or for visualization; or interactively process entire cohorts to find transition/transversion ratios, allelic frequency, genome-wide association and more using BigQuery.
Share genomic data with your research group, collaborators, the broader community, or the public. You decide.
Google Genomics is implementing the API defined by the Global Alliance for Genomics and Health for visualization, analysis and more. Compliant software can access Google Genomics, local servers, or any other implementation.
Cluster computing
https://spark.apache.org/downloads.html
Google BigQuery
https://cloud.google.com/bigquery/what-is-bigquery
Thursday, November 13, 2014
10 New Breakthrough Technologies 2014
http://www.technologyreview.com/lists/technologies/2014/
Agricultural Drones
Ultraprivate Smartphones
Brain Mapping
Neuromorphic Chips
Genome Editing
Microscale 3-D Printing
Mobile Collaboration
Oculus Rift
Agile Robots
Smart Wind and Solar Power
Agricultural Drones
Ultraprivate Smartphones
Brain Mapping
Neuromorphic Chips
Genome Editing
Microscale 3-D Printing
Mobile Collaboration
Oculus Rift
Agile Robots
Smart Wind and Solar Power
Monday, November 10, 2014
Alzheimer's drug sneaks through blood–brain barrier
Neurobiologist Ryan Watts and his colleagues at the biotechnology company Genentech in South San Francisco have sought to break through the barrier by exploiting transferrin, a protein that sits on the surface of blood vessels and carries iron into the brain. The team created an antibody with two ends. One end binds loosely to transferrin and uses the protein to transport itself into the brain. And once the antibody is inside, its other end targets an enzyme called β-secretase 1 (BACE1), which produces amyloid-β. Crucially, the antibody binds more tightly to BACE1 than to transferrin, and this pulls it off the blood vessel and into the brain. It locks BACE1 shut and prevents it from making amyloid-β.
http://www.nature.com/news/alzheimer-s-drug-sneaks-through-blood-brain-barrier-1.16291
http://www.nature.com/news/alzheimer-s-drug-sneaks-through-blood-brain-barrier-1.16291
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